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Texture features in the Shearlet domain for histopathological image classification

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2020
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Mentioned by

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1 tweeter

Citations

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2 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Texture features in the Shearlet domain for histopathological image classification
Published in
BMC Medical Informatics and Decision Making, December 2020
DOI 10.1186/s12911-020-01327-3
Pubmed ID
Authors

Sadiq Alinsaif, Jochen Lang

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 20%
Researcher 1 20%
Student > Doctoral Student 1 20%
Student > Master 1 20%
Unknown 1 20%
Readers by discipline Count As %
Medicine and Dentistry 3 60%
Biochemistry, Genetics and Molecular Biology 1 20%
Unknown 1 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 December 2020.
All research outputs
#15,865,220
of 17,954,410 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,521
of 1,634 outputs
Outputs of similar age
#350,113
of 415,525 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#149
of 168 outputs
Altmetric has tracked 17,954,410 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,634 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 415,525 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.